MS 18

Resilience Modeling for Risk-Informed Decision Support


John W. van de Lindt,

Colorado State University

You Dong,

The Hong Kong Polytechnic University


Resilience is the ability to prepare for, absorb, and recover rapidly from naturally occurring and intentional events. Over the past decade, a substantial body of research worldwide has been accumulated that ranges from modeling of individual facilities for better performance to network models with interdependencies across nodes; and even inter-sector dependencies that provide dependencies across physical systems. More recently full community- and regional-level models have been realized that contain interacting physical, social, and economic systems to enable risk-informed decision support. In this mini-symposium, a series of (at least) three sessions is proposed that explore the application of resilience models for decision support at different scales. Presentations are invited that focus on individual networks and systems such as water networks, transportation systems, and building clusters including how a decision is informed; cross-dependent models; full community- and regional-level modeling; and interdisciplinary analyses that encompass social and economic theory and data. The presentations will be organized to begin the symposium at the detailed and complex-model level of the individual systems to inform decisions, followed by increasing levels of scale with (presumably) decreased levels of resolution or complexity until the entire community and regions are modeled and provide risk-informed decision support. Presentations focusing on all hazards are welcome including (but not limited to) climate change, earthquake, tornado, flood, hurricane/typhoon, wildfire, and human-induced events; all approaches from physics- and processed-based (e.g. discrete event simulation) to data-driven (e.g. machine learning) are welcome.